Spatial Distribution of China’s Industrial Output Values under Global Warming Scenarios RCP4.5 and RCP8.5

Author:

Xue QianORCID,Song WeiORCID

Abstract

Climatic changes significantly impact the socio-economic system. Compared with research on the impacts of climate change on the agricultural economic system, researches on the impacts on the industrial economic system are still scarce. This is mainly because of the difficulties in matching climate data with socio-economic data in terms of spatiotemporal resolution, which has greatly limited the exposure degree assessment and the risk assessment of industrial economic systems. In view of this, based on remote sensing inversion and multi-source data fusion, we generated kilometer-grid data of China’s industrial output in 2010 and built the spatial distribution model of industrial output, based on random forest, to simulate the spatial distribution of China’s industrial output under different climate change scenarios. The results showed that (1) our built spatial distribution simulation model of China’s industrial output under different climate change scenarios had an accuracy of up to 93.77%; (2) from 2010 to 2050, the total growth of China’s industrial output under scenario RCP8.5 is estimated to be 4.797% higher than that under scenario RCP4.5; and (3) the increasing rate of the average annual growth rate of China’s industrial output slows down significantly under both scenarios from 2030 to 2050, and the average annual growth rate will decrease by 7.31 and 6.54%, respectively, under scenarios RCP8.5 and RCP4.5 compared with that from 2010 to 2020.

Publisher

MDPI AG

Subject

Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Geography, Planning and Development

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Investigating Variations in Anthropogenic Heat Flux along Urban–Rural Gradients in 208 Cities in China during 2000–2016;Buildings;2024-09-03

2. Progress of Spatial Geographic Phenomenon Visualization Methods Based on Multi-Source Data;2023 International Conference on Data Science & Informatics (ICDSI);2023-08-12

3. Mapping Global Industrial Value Added;Atlas of Global Change Risk of Population and Economic Systems;2022

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